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The Method of Linear Variations

  In this section we show that the method of linear variations (also called the Ritz method [12]) is equivalent to the matrix formulation tex2html_wrap_inline3586 of the Schrödinger equation tex2html_wrap_inline3588. Our treatment is similar to that of Szabo and Ostlund [1], p. 116. The linear variation method states that, given the linear expansion
 equation509
we vary the coefficients tex2html_wrap_inline3590 so that we minimize tex2html_wrap_inline3592. We begin by requiring that the wavefunction be normalized so that tex2html_wrap_inline3594. Normalization means that we cannot minimize E simply by solving
 equation519
because the tex2html_wrap_inline3590's are not independent. In this case we have a constrained minimization, so we apply Lagrange's method of undetermined multipliers, and we minimize the functional
 equation528
which has the same minimum as E when tex2html_wrap_inline3315 is normalized. When we substitute equation (3.1) into equation (3.3), we obtain
 equation539
which we may rewrite as
 equation551
where of course tex2html_wrap_inline3571 and tex2html_wrap_inline3606. Now set the first variation in tex2html_wrap_inline3608 equal to zero:
 equation568
Since the summations run over all i and j, and since tex2html_wrap_inline3614 and tex2html_wrap_inline3616, we can simplify to
 equation590
Since each term is a sum of a number and its complex conjugate, the imaginary parts will cancel. However, the real part will not necessarily be zero; in fact, since all the tex2html_wrap_inline3618's are arbitrary (that is the whole point of using Lagrange's method), then for tex2html_wrap_inline3620 to be zero, the term in brackets must be zero. We may rewrite this condition as a matrix equation
 equation599
If the basis functions { tex2html_wrap_inline3309 } are chosen orthonormal (as is usually the case), then tex2html_wrap_inline3624 the identity matrix, and we have tex2html_wrap_inline3586. Of course tex2html_wrap_inline3628 is the column-vector representation of tex2html_wrap_inline3315 in the basis { tex2html_wrap_inline3309 }. We thus have two equivalent ways of viewing a CI--either as the matrix formulation of the Schrödinger equation within the given linear vector space of N-electron basis functions, or as the minimization of the energy with respect to the linear expansion coefficients tex2html_wrap_inline3590 of (3.1), subject to the constraint that the wavefunction remain normalized. Another way of viewing the results of this section is to note that only eigenvectors of the Hamiltonian matrix tex2html_wrap_inline3271 are stable with respect to variations in the linear expansion coefficients.

At this point it is reasonable to ask why we wish to minimize the energy by varying the coefficients in equation (3.1). How do we know that this will give us the best estimate of the wavefunction? There are two answers to this. First, as we have just shown, minimizing the energy by variation of the linear expansion coefficients gives the Schrödinger equation in matrix form; thus the procedure is justified a posteriori by the validity of its result. The other reason is that, for the ground state, the linear expansion in equation (3.1) gives an expectation value for the energy E which is always an upper bound to the exact nonrelativistic ground state energy tex2html_wrap_inline3534. We will prove this assertion in the next section; the result is called the Variational Theorem. The best estimate of E, then, is the minimum value which can be obtained by varying the coefficients in equation (3.1) (while also maintaining normalization). These arguments also hold for excited states, so long as each excited state is made orthogonal to all lower states.


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